Fuzzy-Based Multi-Objective Design Optimization of Buried Pipelines

This paper proposes fuzzy-based multi-objective design optimization approach for the optimal analysis of buried pipe based on the expected value of a fuzzy output variable when the membership function is computed. The design of pipe structures is usually associated with uncertainties. Therefore, the principle of fuzzy set and a multi-objective optimization algorithm is applied to account for the variabilities associated with the uncertain parameters to ensure an acceptable performance against the impact of uncertainties. Different methods such as deterministic and non-deterministic methods have been proposed to model the effect of uncertainties and analyse the performance of engineering structure in the literature. Herein, a fuzzy-based uncertainty modelling approach that employs the optimal performance of a hybrid GA-GAM for the analysis of a buried pipeline is proposed. The purpose of the strategy is to optimise the design variable while considering the adverse effect of the uncertain fuzzy variables and variability of the structural performance. The uncertain fuzzy variable is used in the analysis to take into account the subjective nature of the corrosion process, while the entropy of a fuzzy variable used as a global measure of variable dispersion is employed to measure the variability and sensitivity of the structural response. The outcome of the fuzzy-based multi-objective design optimization provides a set of optimal solution for the analysis of fuzzy structure. Finally, the applicability and characteristic of this method are demonstrated using a numerical example, and the outcome denotes acceptable analytical tools for design engineers and can be applied to analyse other engineering structures.

Automated summary

This paper introduces a fuzzy-based multi-objective design optimization approach for handling uncertainty in pipeline structure design. By considering the variability of uncertain parameters and utilizing fuzzy set principles and multi-objective optimization algorithms, acceptable performance can be ensured against uncertainties in structural design.